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حدیث بی آبی سامان آبدانان مهدی زاده مریم نداف زاده محمد رضا صالحی سلمی

چکیده

در زمینه‌ی کشاورزی، نظارت منظم و دوره‌ای جهت کنترل سلامت و کیفیت گیاهان امری ضروری است. اندازه‌گیری مقدار کلروفیل و کارتنوئید برگ به‌عنوان یکی از شاخص‌های سلامت محصول محسوب می‌شود. در این پژوهش مجموعه‌هایی از تصاویر برگ‌های 6 گياه مختلف (ختمی، لگنوم، برگ بیدی، انجیر معابد، رز و کنار) با هدف پیش‌بینی کلروفیل و کارتنوئید در فضاهای رنگی پیشنهادشده (RGB،Lab ،HSV  و I1I2I3) مورد بررسی قرار گرفتند. هر فضای رنگی شرایط مختلفی از احتمال توزیع یک گروه رنگ را ارائه می‌دهد، بدین ترتيب پس از بررسی فضاهای رنگی با توجه به نتایج آناليز آماری در سطح احتمال 5%، مناسب‌ترین پارامترهای رنگی (R، a و c) جهت آموزش الگوریتم درخت تصمیم‌گیری انتخاب گردید. بر اساس نتایج به‌دست‌آمده، نشان داده شد که بين روش پردازش تصوير و مقادیر اندازه‌گیری شده توسط دستگاه طیف‌سنج همبستگي بالای 92/0 برای کلروفیل و 85/0 برای کارتنوئید وجود دارد. همچنین شایان ذکر است که استفاده از روش پیشنهادی این تحقیق می‌تواند هم از لحاظ اقتصادی (هزینه‌های مربوط به نیروی انسانی و تهیه دستگاه اسپد) و هم از نظر صرفه‌جویی در زمان بسیار مقرون به‌صرفه باشد.

جزئیات مقاله

کلمات کلیدی

الگوریتم درخت تصمیم‌گیری, پردازش تصویر, دستگاه اسپد, فضاهای رنگی

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ارجاع به مقاله
بی آبی ح., آبدانان مهدی زاده س., نداف زاده م., & صالحی سلمی م. ر. (2019). طراحی و توسعه سامانه بینایی ماشین به‌منظور پیش‌بینی محتوای کلروفیل و کارتنوئید برگ گیاهان. ماشین‌های کشاورزی, 9(2), 279-293. https://doi.org/10.22067/jam.v9i2.71716
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